10.18710/TEJDSFKaspersen, EivindEivindKaspersen0000-0002-4960-058XNTNU – Norwegian University of Science and TechnologyEye-tracking data for classification of geometric shapesDataverseNO2021Social Scienceseye trackingabstractionstrategiesconceptual thinkinggeometryclassificationKaspersen, EivindEivindKaspersenNTNU – Norwegian University of Science and TechnologyNTNU – Norwegian University of Science and TechnologyNTNU – Norwegian University of Science and TechnologyNTNU – Norwegian University of Science and Technology2021-12-172023-09-284906275471857text/plaintext/plainapplication/vnd.openxmlformats-officedocument.spreadsheetml.sheet1.1CC0 1.0Eye-tracking data for geometric classification tasks for abstract and non-abstract thinking. How to develop and assess abstraction processes are longstanding methodical problems in mathematics education. Recently, the advent of eye tracking technology has spurred a discussion about whether eye movement analysis can support valid inferences about mathematical thinking. In this study, we investigated whether eye tracking can be used to infer whether a person uses abstraction to solve a geometric classification task. The participants were shown three exemplars of either triangles or quadrilaterals (task shapes) in different trials. They were then asked to select all the other shapes belonging to the same class from an array of six geometric shapes (response shapes) while we tracked their eye movements. Finally, we coded each trial by whether participants verbally reported to (i) use an abstract concept or (ii) directly compare task shapes with response shapes to solve the task. We found that concept trials were characterised by eye movements that made few connections between the task shapes and the response shapes and more connections between the response shapes. Non-concept trials were characterised by eye movements that connected task shapes with response shapes as if to compare their similarity directly. A logistic regression model correctly classified the trials as concept or non-concept based on eye-tracking data in 80.3% of the cases. We conclude that eye tracking can contribute to making inferences about mathematical thought processes and facilitate research on abstraction.